Core Insights - Huawei's autonomous driving solution, QianKun Intelligent Driving (ADS), has achieved significant milestones, including 1 million units of delivery and 40 billion kilometers of assisted driving mileage [1][5][9] Group 1: ADS Development and Features - The ADS has undergone three commercial iterations, with ADS 1 launched in 2022 for urban NCA, ADS 2 in 2023 enabling nationwide driving without high-precision maps, and ADS 3 offering end-to-end and parking functionalities [3][5] - The recently released ADS 4 has upgraded its technical architecture and user experience, providing comprehensive support for various driving scenarios, including parking and emergency braking [5][6] - As of July 2023, Huawei's ADS system has over 700,000 active users, with an average assisted driving mileage of nearly 700 kilometers per user in July alone [5][6] Group 2: Future Plans and Market Position - Huawei aims to accelerate the development of L3 and L4 autonomous driving technologies, targeting L3 commercial deployment on highways by 2026 and L4 pilot projects in urban areas by the same year [6] - The company has invested over 10 years in the automotive sector, with R&D expenditures exceeding 10 billion yuan in 2024 and a workforce of 8,000 dedicated to smart vehicle solutions [9] - Huawei's collaboration with automotive manufacturers focuses on empowering state-owned enterprises, enhancing their capabilities in electric and intelligent vehicle transitions [9]

Core Insights - As of July this year, the number of vehicles equipped with Huawei's QianKun intelligent driving system has reached 1 million, with over 10 million instances of parking assistance and a cumulative assisted driving mileage of 4 billion kilometers [1][3] - Huawei's QianKun intelligent driving system has successfully avoided potential collisions 2.54 million times, with an average assisted driving mileage of nearly 700 kilometers per person and an average of 37 parking assists per person [1][3] Industry Overview - The Chinese automotive assisted driving industry is experiencing intense market competition, with a significant reduction in the number of manufacturers compared to 5-6 years ago, indicating a trend towards market concentration [3] - The penetration rate of L2 level assisted driving functions in China was only 19% last year, but it is expected to soar to 50% this year, reflecting strong consumer demand for intelligent features [5] Technological Development - Huawei emphasizes the importance of data-driven technology in the development of assisted driving systems, arguing that the industry is fundamentally a competition of data volume, computing power, and algorithms [3][4] - The company has adopted a one-step end-to-end approach for its technology, which is seen as a more challenging but ultimately superior path compared to other manufacturers' visual language action models [3] Product Collaboration - Huawei has partnered with 28 vehicle models, including brands like Audi, Avita, and others, covering a wide range of vehicle types and price points, which has led to significant sales growth for its partners [5] - The collaboration with Audi signifies that luxury brands will increasingly consider intelligent features, presenting an opportunity for Chinese automakers to transition from mid-range to high-end markets [5] User Experience and Innovation - Huawei's MoLA architecture aims to integrate applications, hardware, and devices to enhance user experience, with features like a high-power audio system and AI assistants [6] - The company believes that a fragmented supply chain can lead to poor user experiences, thus it focuses on providing a cohesive system to ensure long-term satisfaction [6] Strategic Focus - Huawei's strategy is centered on long-term investment and user-centric development, with over 10 years of investment in its automotive business leading to current profitability [8][9] - The company prioritizes product quality and delivery in collaboration with partners, emphasizing that consumer perception of value is the key measure of success [9]